Probabilistic models for decision support under climate change:

Transcription

1 Probabilistic models for decision support under climate change: An example using bull trout in the Boise River basin Douglas Peterson 1 US Fish and Wildlife Service Abernathy Fish Technology Center Longview, Washington Doug_Peterson@fws.gov March 1, Former address: USFWS, Montana Ecological Services, Helena, Montana

2 Probabilistic models for decision support under climate change: Acknowledgements: Bruce Rieman, RMRS retired Seth Wenger, Trout Unlimited Dan Isaak, RMRS-Boise Dona Horan, RMRS-Boise 2

3 How do we use all this stuff? Bringing it all together Decision space and uncertainty Prediction error, complexity, non-stationarity Linking data to a decision framework Bayesian network (BN) approach Example: Bull trout in the Boise River basin Building a model Predictions and lessons learned 3

4 Uncertainty: prediction error Air temperature Precipitation Air temperature and precipitation trends across the western US, (Mote et al. 2005) Global climate change scenarios based on different assumptions for greenhouse gas emissions and human economic trends (Fig. SPM5, from IPCC 2007, Working Group I). 4

5 Uncertainty: complexity What does climate change do to an already complex problem? Peterson et al (2008) 5

6 Uncertainty: non-stationarity How long before these scenarios become obselete? Will important ecological relationships hold, as we understand them now? Will statistical relationships used to model climate variables continue to hold? Isaak et al (2009) 6

7 Uncertainty: error propagation 7

8 Bayesian networks (BNs) in use 8

9 Bayesian Networks: definition & properties BBNs: graphical models that incorporates probabilistic relationships among variables of interest (Jensen 2001) Useful attributes: Logical Probabilistic Transparent Adaptable Spatial representation Management interventions Portable knowledge format (Conrady and Jouffe 2011) BBN predicting brown trout density from a suite of environmental, management, and land use factors (from Borsuk et al. 2006) 9

10 Bull trout in the Boise River basin 10

11 Concept: climate impacts on populations Global or Regional Climate Models (+ error) Downscaled climate predictions (+ error) Biotic Context (+ error) Landscape Context (+ error) a MODEL VULNERABILITY OR PERSISTENCE 11

12 Conceptual model of vulnerability Human Disruption Climate Predictions Landscape Context Temperature Regime Flow Regime Disturbance Regime Biotic Context Habitat Suitability Habitat Extent Connectivity and adjacent populations Population Growth rate Sensitivity to Catastrophic Events Population Vulnerability Influence diagram depicting linkages between climate, environmental context, and human disruption on vulnerability of stream salmonid populations (adapted from Rieman and Isaak 2010). Orange boxes represent variables considered for the Boise River basin bull trout example. 12

13 Influence diagram Landscape context Disturbance Biotic context PREDICTION 13

14 Parameterized model Summer Mean Flow Gradient <2 % gradient % gradient 33.3 >8% gradient ± 0.11 Winter High Flow w95 <1 event per winter events per winter 33.3 >4 events per winter ± 14 Water Temperature <7 degrees C degrees C degrees C degrees C 20.0 >18 degrees C ± 7.3 Stream Size <1m width m width m width 25.0 >8m width ± 6.9 <0.2 cfs to 1.19 cfs to 43.3 cfs 25.0 >43.3 cfs ± 260 Bed Scour <1 event per winter 1-4 events per winter >4 events per winter Brook trout Physical Habitat Suitability Low Moderate High Bull trout Physical Habitat Suitability Low Moderate High Brook trout occurrence Present Absent Bull trout Survival egg to age-2 emigrant Negative Positive Probability of bull trout occurrence in re... Absent Present Brook trout source population No Yes

15 Data integration mean summer water temperature Juvenile bull trout occurrence Rieman and Chandler (1999) BBN states for bull trout Wenger et al (in review) Water Temperature <7 degrees C 7-10 degrees C degrees C degrees C >18 degrees C 13 ± Ideal Ideal Suitable Marginal Poor Isaak et al. (2010) Stream temperature thresholds based on empirical observations, statistical models, and controlled experiments. Other BBN variables developed using the same approach. McMahon et al (2007)

16 Parameterized model Summer Mean Flow Gradient <2 % gradient % gradient 33.3 >8% gradient ± 0.11 Winter High Flow w95 <1 event per winter events per winter 33.3 >4 events per winter ± 14 Water Temperature <7 degrees C degrees C degrees C degrees C 20.0 >18 degrees C ± 7.3 Stream Size <1m width m width m width 25.0 >8m width ± 6.9 <0.2 cfs to 1.19 cfs to 43.3 cfs 25.0 >43.3 cfs ± 260 Bed Scour <1 event per winter 1-4 events per winter >4 events per winter Brook trout Physical Habitat Suitability Low Moderate High Bull trout Physical Habitat Suitability Low Moderate High Brook trout occurrence Present Absent Bull trout Survival egg to age-2 emigrant Negative Positive Probability of bull trout occurrence in re... Absent Present Brook trout source population No Yes

17 Prediction based on input data Summer Mean Flow Gradient <2 % gradient 0 2-8% gradient 100 >8% gradient ± Winter High Flow w95 <1 event per winter events per winter 100 >4 events per winter ± 0.87 Water Temperature <7 degrees C degrees C degrees C degrees C 0 >18 degrees C ± 0.87 Stream Size <1m width 0 1-2m width 0 2-8m width 100 >8m width 0 5 ± 1.7 <0.2 cfs to 1.19 cfs to 43.3 cfs 100 >43.3 cfs ± 12 Bed Scour <1 event per winter 1-4 events per winter >4 events per winter Brook trout Physical Habitat Suitability Low Moderate High Bull trout Physical Habitat Suitability Low Moderate High Brook trout occurrence Present Absent Bull trout Survival egg to age-2 emigrant Negative Positive Probability of bull trout occurrence in re... Absent Present Brook trout source population No Yes

18 Applying the model: bull trout in the Boise R. basin Global Climate Model A1B (historical, 2040s, 2080s) Brook trout (yes, no) Stream temperature (Isaak et al. 2010) Stream flow - VIC (Wenger et al. 2010) Gradient BN model ~1400 NHD+ segment-scale predictions Map using GIS 18

19 Climate change no brook trout 1. Historical

20 Historical no brook trout

21 2046 no brook trout

22 2086 no brook trout

23 Climate change + brook trout no brook trout brook trout present 23

24 2046 no brook trout

25 2046 brook trout present

26 2046 no brook trout

27 2046 brook trout present

28 Predictions - intuitive Stream water temperature very important! or Stream temperature model: Isaak et al. (2010) BN model Is the BN worth the extra effort? 28

29 Headwaters

30 Predictions counter intuitive Isaak et al. (2010) BBN model Brook trout effect nil when winter flooding increases and habitat favors bull trout Habitat shrinking from both directions 30

31 Summary Bayesian networks are useful framework to integrate data and assess climate impacts given uncertainty Outcomes Decision support tool Process 31

32 References Borsuk et al Assessing the decline of brown trout (Salmo trutta) in Swiss rivers using a Bayesian probability network. Ecological Modelling 192: doi: /j.ecolmodel Conrady, S. and L. Jouffe Introduction to Bayesian networks: practical and technical perspectives. Available: Isaak, D.J. et al A watershed-scale monitoring protocol for bull trout. Gen. Tech. Rep. RMRS-GTR-224. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 25 p. Available: Isaak, D.J. et al Effects of climate change and recent wildfires on stream temperature and thermal habitat for two salmonids in a mountain river network. Ecological Applications. 20(5): doi: / McMahon, T.E., et al Temperature and competition between bull trout and brook trout: a test of the elevation refuge hypothesis. Transactions of the American Fisheries Society 136: doi: /T Mote, P.W. et al Declining mountain snowpack in western North America. Bulletin of the American Meteorological Society. 86: doi: /BAMS Newton, A.C Use of a Bayesian network for Red Listing under uncertainty. Environmental Modelling and Software 25: doi: /j.envsoft Peterson, D.P. et al Analysis of trade-offs between threats of invasion by nonnative brook trout (Salvelinus fontinalis) and intentional isolation for native westslope cutthroat trout (Oncorhynchus clarkii lewisi). Canadian Journal of Fisheries and Aquatic Sciences 65: doi: /f Intergovernmental Panel on Climate Change (IPCC) Climate change 2007: the physical science basis. Available: Jensen, F.V Bayesian networks and decision graphs. Springer-Verlag. Rieman, B.E. and G. Chandler Empirical evaluation of temperature effects on bull trout distribution in the Northwest. USFS Rocky Mountain Research Station, Final Report to US EPA No Boise, Idaho. Available: Rieman, B.E. et al Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River Basin. Forest Ecology and Management 153: Rieman, B.E. and D.J. Isaak Climate change, aquatic ecosystems, and fishes in the Rocky Mountain West: implications and alternatives for management. Gen. Tech. Rep. RMRS-GTR-250. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 46 p. available: Wenger, S.J. et al Macroscale hydrologic modeling of ecologically relevant flow metrics. Water Resources Research 46: W09513, doi: /2009wr Wenger, S.J. et al. In review. Role of climate and invasive species in structuring trout distributions in the Interior Columbia Basin. Submitted to Canadian Journal of Fisheries and Aquatic Sciences 32